IBM scientists propose a linear-complexity search tool that avoids wasteful and repetitive computations and reduces the average time complexity to linear - potential applications include addressing fake news.

CellCycleTRACER is a supervised machine learning algorithm which classifies and sorts single-cell mass cytometry data according to their cell cycle, and enables correction for cell-cycle-state and cell-volume heterogeneity – essentially...

Today, IBM Research is announcing that its scientists have demonstrated that an unsupervised machine-learning algorithm, running on one million phase change memory (PCM) devices, successfully found temporal correlations in unknown...